In the monolithic detection, a classifier for the whole object appearance is trained using a set of training images. This approach typically employs features such as Haar wavelets, gradient-based features such as histograms of oriented gradient (HOG) feature [1]}, edgelets [2]} or shapelets [3]}, to represent the whole object appearance. These methods, like [4]}, [5]}, [6]}, are helpful in sparse scenes but suffer in settings having many objects with occlusions and clutters.
